Fast and effective prediction of microRNA/target duplexes

Mammalian microRNAs: a small world for fine-tuning gene expression

The basis of eukaryotic complexity is an intricate genetic architecture where parallel systems are involved in tuning gene expression, via RNA-DNA, RNA-RNA, RNA-protein, and DNA-protein interactions. In higher organisms, about 97% of the transcriptional output is represented by noncoding RNA (ncRNA) encompassing not only rRNA, tRNA, introns, 5′ and 3′ untranslated regions, transposable elements, and intergenic regions, but also a large, rapidly emerging family named microRNAs. MicroRNAs are short 20-22-nucleotide RNA molecules that have been shown to regulate the expression of other genes in a variety of eukaryotic systems. MicroRNAs are formed from larger transcripts that fold to produce hairpin structures and serve as substrates for the cytoplasmic Dicer, a member of the RNase III enzyme family. A recent analysis of the genomic location of human microRNA genes suggested that 50% of microRNA genes are located in cancer-associated genomic regions or in fragile sites. This review focuses on the possible implications of microRNAs in post-transcriptional gene regulation in mammalian diseases, with particular focus on cancer. We argue that developing mouse models for deleted and/or overexpressed microRNAs will be of invaluable interest to decipher the regulatory networks where microRNAs are involved.

Overgrowth caused by misexpression of a microRNA with dispensable wild-type function

MicroRNAs (miRNAs) represent an abundant class of non-coding RNAs that negatively regulate gene expression, primarily at the post-transcriptional level. miRNA genes are frequently located in proximity to fragile chromosomal sites associated with cancers and amplification of a miRNA cluster has been correlated with the etiology of lymphomas and solid tumors. The oncogenic potential of a miRNA polycistron has recently been demonstrated in vivo. Here, we show that misexpression of the Drosophila miRNA mirvana/mir-278 in the developing eye causes massive overgrowth, in part due to inhibition of apoptosis. A single base substitution affecting the mature miRNA blocks the gain-of-function phenotype but is not associated with a detectable reduction-of-function phenotype when homozygous. This result demonstrates that misexpressed miRNAs may acquire novel functions that cause unscheduled proliferation in vivo and thus exemplifies the potential of miRNAs to promote tumor formation.

miRBase: microRNA sequences, targets and gene nomenclature

The miRBase database aims to provide integrated interfaces to comprehensive microRNA sequence data, annotation and predicted gene targets. miRBase takes over functionality from the microRNA Registry and fulfils three main roles: the miRBase Registry acts as an independent arbiter of microRNA gene nomenclature, assigning names prior to publication of novel miRNA sequences. miRBase Sequences is the primary online repository for miRNA sequence data and annotation. miRBase Targets is a comprehensive new database of predicted miRNA target genes. miRBase is available at .

miRNAMap: genomic maps of microRNA genes and their target genes in mammalian genomes

Recent work has demonstrated that microRNAs (miRNAs) are involved in critical biological processes by suppressing the translation of coding genes. This work develops an integrated database, miRNAMap, to store the known miRNA genes, the putative miRNA genes, the known miRNA targets and the putative miRNA targets. The known miRNA genes in four mammalian genomes such as human, mouse, rat and dog are obtained from miRBase, and experimentally validated miRNA targets are identified in a survey of the literature. Putative miRNA precursors were identified by RNAz, which is a non-coding RNA prediction tool based on comparative sequence analysis. The mature miRNA of the putative miRNA genes is accurately determined using a machine learning approach, mmiRNA. Then, miRanda was applied to predict the miRNA targets within the conserved regions in 3'-UTR of the genes in the four mammalian genomes. The miRNAMap also provides the expression profiles of the known miRNAs, cross-species comparisons, gene annotations and cross-links to other biological databases. Both textual and graphical web interface are provided to facilitate the retrieval of data from the miRNAMap. The database is freely available at http://mirnamap.mbc.nctu.edu.tw/.

The microRNA miR-181 targets the homeobox protein Hox-A11 during mammalian myoblast differentiation

Deciphering the mechanisms underlying skeletal muscle-cell differentiation in mammals is an important challenge. Cell differentiation involves complex pathways regulated at both transcriptional and post-transcriptional levels. Recent observations have revealed the importance of small (20-25 base pair) non-coding RNAs (microRNAs or miRNAs) that are expressed in both lower organisms and in mammals. miRNAs modulate gene expression by affecting mRNA translation or stability. In lower organisms, miRNAs are essential for cell differentiation during development; some miRNAs are involved in maintenance of the differentiated state. Here, we show that miR-181, a microRNA that is strongly upregulated during differentiation, participates in establishing the muscle phenotype. Moreover, our results suggest that miR-181 downregulates the homeobox protein Hox-A11 (a repressor of the differentiation process), thus establishing a functional link between miR-181 and the complex process of mammalian skeletal-muscle differentiation. Therefore, miRNAs can be involved in the establishment of a differentiated phenotype - even when they are not expressed in the corresponding fully differentiated tissue.

Animal MicroRNAs confer robustness to gene expression and have a significant impact on 3'UTR evolution

MicroRNAs are small noncoding RNAs that serve as posttranscriptional regulators of gene expression in higher eukaryotes. Their widespread and important role in animals is highlighted by recent estimates that 20%-30% of all genes are microRNA targets. Here, we report that a large set of genes involved in basic cellular processes avoid microRNA regulation due to short 3'UTRs that are specifically depleted of microRNA binding sites. For individual microRNAs, we find that coexpressed genes avoid microRNA sites, whereas target genes and microRNAs are preferentially expressed in neighboring tissues. This mutually exclusive expression argues that microRNAs confer accuracy to developmental gene-expression programs, thus ensuring tissue identity and supporting cell-lineage decisions.

TarBase: A comprehensive database of experimentally supported animal microRNA targets

MicroRNAs (miRNAs) are approximately 22-nt RNA segments that are involved in the regulation of protein expression primarily by binding to one or more target sites on an mRNA transcript and inhibiting translation. MicroRNAs are likely to factor into multiple developmental pathways, multiple mechanisms of gene regulation, and underlie an array of inherited disease processes and phenotypic determinants. Several computational programs exist to predict miRNA targets in mammals, fruit flies, worms, and plants. However, to date, there is no systematic collection and description of miRNA targets with experimental support. We describe a database, TarBase, which houses a manually curated collection of experimentally tested miRNA targets, in human/mouse, fruit fly, worm, and zebrafish, distinguishing between those that tested positive and those that tested negative. Each positive target site is described by the miRNA that binds it, the gene in which it occurs, the nature of the experiments that were conducted to test it, the sufficiency of the site to induce translational repression and/or cleavage, and the paper from which all these data were extracted. Additionally, the database is functionally linked to several other useful databases such as Gene Ontology (GO) and UCSC Genome Browser. TarBase reveals significantly more experimentally supported targets than even recent reviews claim, thereby providing a comprehensive data set from which to assess features of miRNA targeting that will be useful for the next generation of target prediction programs. TarBase can be accessed at http://www.diana.pcbi.upenn.edu/tarbase.

Thermodynamics of RNA-RNA binding

BACKGROUND

Reliable prediction of RNA-RNA binding energies is crucial, e.g. for the understanding on RNAi, microRNA-mRNA binding and antisense interactions. The thermodynamics of such RNA-RNA interactions can be understood as the sum of two energy contributions: (1) the energy necessary to 'open' the binding site and (2) the energy gained from hybridization.

METHODS

We present an extension of the standard partition function approach to RNA secondary structures that computes the probabilities Pu[i, j] that a sequence interval [i, j] is unpaired.

RESULTS

Comparison with experimental data shows that Pu[i, j] can be applied as a significant determinant of local target site accessibility for RNA interference (RNAi). Furthermore, these quantities can be used to rigorously determine binding free energies of short oligomers to large mRNA targets. The resource consumption is comparable with a single partition function computation for the large target molecule. We can show that RNAi efficiency correlates well with the binding energies of siRNAs to their respective mRNA target.

AVAILABILITY

RNAup will be distributed as part of the Vienna RNA Package, www.tbi.univie.ac.at/~ivo/RNA/

GUUGle: a utility for fast exact matching under RNA complementary rules including G-U base pairing

MOTIVATION

RNA secondary structure analysis often requires searching for potential helices in large sequence data.

RESULTS

We present a utility program GUUGle that efficiently locates potential helical regions under RNA base pairing rules, which include Watson-Crick as well as G-U pairs. It accepts a positive and a negative set of sequences, and determines all exact matches under RNA rules between positive and negative sequences that exceed a specified length. The GUUGle algorithm can also be adapted to use a precomputed suffix array of the positive sequence set. We show how this program can be effectively used as a filter preceding a more computationally expensive task such as miRNA target prediction.

AVAILABILITY

GUUGle is available via the Bielefeld Bioinformatics Server at http://bibiserv.techfak.uni-bielefeld.de/guugle

MicroRNA function and mechanism: insights from zebra fish

MicroRNAs (miRNAs) are small RNAs that bind to the 3 UTR of mRNAs. We are using zebra fish as a model system to study the developmental roles of miRNAs and to determine the mechanisms by which miRNAs regulate target mRNAs. We generated zebra fish embryos that lack the miRNA-processing enzyme Dicer. Mutant embryos are devoid of mature miRNAs and have morphogenesis defects, but differentiate multiple cell types. Injection of miR-430 miRNAs, a miRNA family expressed at the onset of zygotic transcription, rescues the early morphogenesis defects in dicer mutants. miR-430 accelerates the decay of hundreds of maternal mRNAs and induces the deadenylation of target mRNAs. These studies suggest that miRNAs are not obligatory components of all fate specification or signaling pathways but facilitate developmental transitions and induce the deadenylation and decay of hundreds of target mRNAs.

MicroRNAs and their regulatory roles in animals and plants

microRNAs (miRNAs) are an abundant class of newly identified endogenous non-protein-coding small RNAs. They exist in animals, plants, and viruses, and play an important role in gene silencing. Translational repression, mRNA cleavage, and mRNA decay initiated by miRNA-directed deadenylation of targeted mRNAs are three mechanisms of miRNA-guided gene regulation at the post-transcriptional levels. Many miRNAs are highly conserved in animals and plants, suggesting that they play an essential function in plants and animals. Lots of investigations indicate that miRNAs are involved in multiple biological processes, including stem cell differentiation, organ development, phase change, signaling, disease, cancer, and response to biotic and abiotic environmental stresses. This review provides a general background and current advance on the discovery, history, biogenesis, genomics, mechanisms, and functions of miRNAs.

miRBase: microRNA sequences, targets and gene nomenclature

The miRBase database aims to provide integrated interfaces to comprehensive microRNA sequence data, annotation and predicted gene targets. miRBase takes over functionality from the microRNA Registry and fulfils three main roles: the miRBase Registry acts as an independent arbiter of microRNA gene nomenclature, assigning names prior to publication of novel miRNA sequences. miRBase Sequences is the primary online repository for miRNA sequence data and annotation. miRBase Targets is a comprehensive new database of predicted miRNA target genes. miRBase is available at http://microrna.sanger.ac.uk/.

RNA editing of human microRNAs

BACKGROUND

MicroRNAs (miRNAs) are short RNAs of around 22 nucleotides that regulate gene expression. The primary transcripts of miRNAs contain double-stranded RNA and are therefore potential substrates for adenosine to inosine (A-to-I) RNA editing.

RESULTS

We have conducted a survey of RNA editing of miRNAs from ten human tissues by sequence comparison of PCR products derived from matched genomic DNA and total cDNA from the same individual. Six out of 99 (6%) miRNA transcripts from which data were obtained were subject to A-to-I editing in at least one tissue. Four out of seven edited adenosines were in the mature miRNA and were predicted to change the target sites in 3' untranslated regions. For a further six miRNAs, we identified A-to-I editing of transcripts derived from the opposite strand of the genome to the annotated miRNA. These miRNAs may have been annotated to the wrong genomic strand.

CONCLUSION

Our results indicate that RNA editing increases the diversity of miRNAs and their targets, and hence may modulate miRNA function.

RNA editing of human microRNAs

BACKGROUND

MicroRNAs (miRNAs) are short RNAs of around 22 nucleotides that regulate gene expression. The primary transcripts of miRNAs contain double-stranded RNA and are therefore potential substrates for adenosine to inosine (A-to-I) RNA editing.

RESULTS

We have conducted a survey of RNA editing of miRNAs from ten human tissues by sequence comparison of PCR products derived from matched genomic DNA and total cDNA from the same individual. Six out of 99 (6%) miRNA transcripts from which data were obtained were subject to A-to-I editing in at least one tissue. Four out of seven edited adenosines were in the mature miRNA and were predicted to change the target sites in 3' untranslated regions. For a further six miRNAs, we identified A-to-I editing of transcripts derived from the opposite strand of the genome to the annotated miRNA. These miRNAs may have been annotated to the wrong genomic strand.

CONCLUSION

Our results indicate that RNA editing increases the diversity of miRNAs and their targets, and hence may modulate miRNA function.

The role of microRNA genes in papillary thyroid carcinoma

Apart from alterations in the RET/PTC-RAS-BRAF pathway, comparatively little is known about the genetics of papillary thyroid carcinoma (PTC). We show that numerous microRNAs (miRNAs) are transcriptionally up-regulated in PTC tumors compared with unaffected thyroid tissue. A set of five miRNAs, including the three most up-regulated ones (miR-221, -222, and -146), distinguished unequivocally between PTC and normal thyroid. Additionally, miR-221 was up-regulated in unaffected thyroid tissue in several PTC patients, presumably an early event in carcinogenesis. Tumors in which the up-regulation (11- to 19-fold) of miR-221, -222, and -146 was strongest showed dramatic loss of KIT transcript and Kit protein. In 5 of 10 such cases, this down expression was associated with germline single-nucleotide changes in the two recognition sequences in KIT for these miRNAs. We conclude that up-regulation of several miRs and regulation of KIT are involved in PTC pathogenesis, and that sequence changes in genes targeted by miRNAs can contribute to their regulation.

Computational analysis of microRNA targets in Caenorhabditis elegans

MicroRNAs (miRNAs) are endogenous approximately 22-nucleotide (nt) non-coding RNAs that post-transcriptionally regulate the expression of target genes via hybridization to target mRNA. Using known pairs of miRNA and target mRNA in Caenorhabditis elegans, we first performed computational analysis for specific hybridization patterns between these two RNAs. We counted the numbers of perfectly complementary dinucleotide sequences and calculated the free energy within complementary base pairs of each dinucleotide, observed by sliding a 2-nt window along all nucleotides of the miRNA-mRNA duplex. We confirmed not only strong base pairing within the 5' region of miRNAs (nts 1-8) in C. elegans, but also the required mismatch within the central region (nt 9 or nt 10), and we found weak binding within the 3' region (nts 13-14). We also predicted 687 possible miRNA target transcripts, many of which are thought to be involved in C. elegans development, by combining the above mentioned hybridization tendency with the following analyses: (1) prediction of the miRNA-mRNA duplex with free-energy minimization; (2) identification of the complementary pattern within the miRNA-mRNA duplex; (3) conservation of target sites between C. elegans and C. briggsae, a related soil nematode; and (4) extraction of mRNA candidates with multiple target sites. Rigorous tests using shuffled miRNA controls supported these predictions. Our results suggest that miRNAs recognize their target mRNAs by their hybridization pattern and that many target mRNAs may be regulated through a combination of several specific miRNA target sites in C. elegans.

MicroRNA modulation of megakaryoblast fate involves cholinergic signaling

MicroRNAs (miRNAs) are abundant small regulatory RNAs with multiple roles in cell fate determination. The processes regulating cellular miRNA levels are still unclear and experimental oligonucleotide tools to readily mimic their effects are not yet available. Here, we report that thapsigargin-induced intracellular Ca(++) release suppressed pre-miR-181a levels in human promegakaryotic Meg-01 cells, induced differentiation-associated nuclear endoreduplication and caspase-3 activation and replaced the acetylcholinesterase 3' splice variant AChE-S with AChE-R. AChE, PKC and PKA inhibitors all attenuated the pre-miR-181a decline and the induced differentiation. AChmiON, a synthetic 23-mer 2'-oxymethylated oligonucleotide mimicking the miR-181a sequence, blocked the calcium-induced differentiation while elevating cellular pre-miR-181a levels and inducing DNA fragmentation and cell death. Moreover, when added to RW 264.7 macrophages, AChmiON at 100 nM induced nitric oxide production with efficiency close to that of bacterial endotoxin, demonstrating physiologically relevant activities also in blood-born monocytes/macrophages. The stress-induced modulation of hematopoietic miR-181a levels through AChE, PKC and PKA cascade(s) suggests using miRNA mimics for diverting the fate of hematopoietic tumor cells towards differentiation and/or apoptosis.

MicroRNAs: Small regulators with a big impact

MicroRNAs (miRNA) are non-coding small (approximately 22nt) RNAs that regulate diverse physiological and developmental processes. In animals, they regulate target genes by binding imperfectly to 3'UTR sequences in mRNAs and attenuate translation. There are hundreds of miRNA genes in animals, and current studies show they constitute a minimum of 1% of known genes. We are just beginning to understand the diverse roles they play in cellular processes, which include signaling pathways, developmental pathways, and possibly various types of cancers.

Targets for human encoded microRNAs in HIV genes

MicroRNAs (miRNAs) are increasingly being shown to play vital roles in development, apoptosis, and oncogenesis by interfering with gene expression at the post-transcriptional level. miRNAs, in principle, can contribute to the repertoire of host pathogen interactions during HIV-1 infection. Using a consensus scoring approach, high scoring miRNA-target pairs were selected which were identified by four well-established target prediction softwares. While hsa-mir-29a and 29b target the nef gene, hsa-mir-149 targets the vpr gene, hsa-mir-378 targets env, and hsa-mir-324-5p targets the vif gene. Not only were the minimum free energy values lowest for the bound complex, but also, the rules so far observed for microRNA-target pairing, viz., a continuous stretch of 6-7 base pairing towards the 5' end of the miRNA and incomplete complementarity with the target sequence, were found to be valid. The target regions were highly conserved across the various clades of HIV-1. microRNA expression profiles from previously reported microarray based experiments show that the five human miRNAs are expressed in T-cells, the normal site of infection of HIV-1 virus. This is the first report of human microRNAs which can target crucial HIV-1 genes including the nef gene, which plays an important role in delayed disease progression.

Human microRNA (miR29b) expression controls the amount of branched chain alpha-ketoacid dehydrogenase complex in a cell

Branched chain amino acids (BCAAs) play critical roles in cell and tissue functions in addition to being important components of protein structure. The multifunctional roles speak to the need for maintaining tight control of their concentration within cells. As the BCAA cannot be made de novo in mammals, their cellular concentration is a function of dietary intake, endogenous protein turnover and catabolism of the three amino acids. The branched chain alpha-ketoacid dehydrogenase (BCKD) complex commits the BCAA to degradation and thus is vital in controlling their concentration within a cell. In mammals, BCKD activity state depends on the presence of a covalently bound phosphate on one protein component of the complex. Phosphate is added to the protein through the action of the complex-specific kinase and results in BCKD inactivation. Here, we demonstrate that another reaction plays a role in determining the total amount of BCKD present in a cell. The microRNA (miR29b) molecule tested is targeted to the mRNA for the dihydrolipoamide branched chain acyltransferase component of BCKD and prevents translation when bound. This is the first demonstration of the use of a microRNA to exert control on a metabolic pathway of amino acid catabolism in mammals and offers an explanation for the observed differences in the amount of the BCKD complex present in different tissues and under varying nutritional states.

Prediction and validation of microRNAs and their targets

MicroRNAs are short non-coding RNAs that inhibit translation of target genes by binding to their mRNAs, and have been shown to play a central role in gene regulation in health and disease. Sophisticated computer-based prediction approaches of microRNAs and of their targets, and effective biological validation techniques for validating these predictions, now play a central role in discovery of microRNAs and elucidating their functions.

Versatile and declarative dynamic programming using pair algebras

Background

Dynamic programming is a widely used programming technique in bioinformatics. In sharp contrast to the simplicity of textbook examples, implementing a dynamic programming algorithm for a novel and non-trivial application is a tedious and error prone task. The algebraic dynamic programming approach seeks to alleviate this situation by clearly separating the dynamic programming recurrences and scoring schemes.

Results

Based on this programming style, we introduce a generic product operation of scoring schemes. This leads to a remarkable variety of applications, allowing us to achieve optimizations under multiple objective functions, alternative solutions and backtracing, holistic search space analysis, ambiguity checking, and more, without additional programming effort. We demonstrate the method on several applications for RNA secondary structure prediction.

Conclusion

The product operation as introduced here adds a significant amount of flexibility to dynamic programming. It provides a versatile testbed for the development of new algorithmic ideas, which can immediately be put to practice.

Antisense-mediated depletion reveals essential and specific functions of microRNAs in Drosophila development

MicroRNAs are small noncoding RNAs that control gene function posttranscriptionally through mRNA degradation or translational inhibition. Much has been learned about the processing and mechanism of action of microRNAs, but little is known about their biological function. Here, we demonstrate that injection of 2'O-methyl antisense oligoribonucleotides into early Drosophila embryos leads to specific and efficient depletion of microRNAs and thus permits systematic loss-of-function analysis in vivo. Twenty-five of the forty-six embryonically expressed microRNAs show readily discernible defects; pleiotropy is moderate and family members display similar yet distinct phenotypes. Processes under microRNA regulation include cellularization and patterning in the blastoderm, morphogenesis, and cell survival. The largest microRNA family in Drosophila (miR-2/6/11/13/308) is required for suppressing embryonic apoptosis; this is achieved by differential posttranscriptional repression of the proapoptotic factors hid, grim, reaper, and sickle. Our findings demonstrate that microRNAs act as specific and essential regulators in a wide range of developmental processes.

The effect of U1 snRNA binding free energy on the selection of 5' splice sites

The importance of U1 snRNA binding free energy in the regulation of alternative splicing has been studied in some genes with site-directed mutagenesis. Here we report a large-scale analysis of its impact on 5' splice site (5'ss) selection in human genome. The results show that free energy exerts different effects on alternative 5'ss choice in different situations and -8.1 kcal/mol is a threshold. When both free energies of two competing 5'ss are larger than -8.1 kcal/mol, the 5'ss with lower free energy is more frequently used. However, in other pairs of 5'ss, lower-free-energy 5'ss does not seem to be favored and even the other 5'ss is used more frequently, which suggests that very low binding free energy would impair splicing. Some observations hold true only for those alternative 5' splicing with short alternative exons (<50nt), which implies a complex mechanism of 5'ss selection involving both U1 snRNA binding free energy and regulatory factors.

miRU: an automated plant miRNA target prediction server

MicroRNAs (miRNAs) play important roles in gene expression regulation in animals and plants. Since plant miRNAs recognize their target mRNAs by near-perfect base pairing, computational sequence similarity search can be used to identify potential targets. A web-based integrated computing system, miRU, has been developed for plant miRNA target gene prediction in any plant, if a large number of sequences are available. Given a mature miRNA sequence from a plant species, the system thoroughly searches for potential complementary target sites with mismatches tolerable in miRNA–target recognition. True or false positives are estimated based on the number and type of mismatches in the target site, and on the evolutionary conservation of target complementarity in another genome which can be selected according to miRNA conservation. The output for predicted targets, ordered by mismatch scores, includes complementary sequences with mismatches highlighted in colors, original gene sequences and associated functional annotations. The miRU web server is available at .

Specific effects of microRNAs on the plant transcriptome

Most plant microRNAs (miRNAs) have perfect or near-perfect complementarity with their targets. This is consistent with their primary mode of action being cleavage of target mRNAs, similar to that induced by perfectly complementary small interfering RNAs (siRNAs). However, there are natural targets with up to five mismatches. Furthermore, artificial siRNAs can have substantial effects on so-called off-targets, to which they have only limited complementarity. By analyzing the transcriptome of plants overexpressing different miRNAs, we have deduced a set of empirical parameters for target recognition. Compared to artificial siRNAs, authentic plant miRNAs appear to have much higher specificity, which may reflect their coevolution with the remainder of the transcriptome. We also demonstrate that miR172, previously thought to act primarily by translational repression, can efficiently guide mRNA cleavage, although the effects on steady-state levels of target transcripts are obscured by strong feedback regulation. This finding unifies the view of plant miRNA action.

Weighted sequence motifs as an improved seeding step in microRNA target prediction algorithms

We present a new microRNA target prediction algorithm called TargetBoost, and show that the algorithm is stable and identifies more true targets than do existing algorithms. TargetBoost uses machine learning on a set of validated microRNA targets in lower organisms to create weighted sequence motifs that capture the binding characteristics between microRNAs and their targets. Existing algorithms require candidates to have (1) near-perfect complementarity between microRNAs' 5' end and their targets; (2) relatively high thermodynamic duplex stability; (3) multiple target sites in the target's 3' UTR; and (4) evolutionary conservation of the target between species. Most algorithms use one of the two first requirements in a seeding step, and use the three others as filters to improve the method's specificity. The initial seeding step determines an algorithm's sensitivity and also influences its specificity. As all algorithms may add filters to increase the specificity, we propose that methods should be compared before such filtering. We show that TargetBoost's weighted sequence motif approach is favorable to using both the duplex stability and the sequence complementarity steps. (TargetBoost is available as a Web tool from http://www.interagon.com/demo/.).

microRNA target predictions across seven Drosophila species and comparison to mammalian targets

microRNAs are small noncoding genes that regulate the protein production of genes by binding to partially complementary sites in the mRNAs of targeted genes. Here, using our algorithm PicTar, we exploit cross-species comparisons to predict, on average, 54 targeted genes per microRNA above noise in Drosophila melanogaster. Analysis of the functional annotation of target genes furthermore suggests specific biological functions for many microRNAs. We also predict combinatorial targets for clustered microRNAs and find that some clustered microRNAs are likely to coordinately regulate target genes. Furthermore, we compare microRNA regulation between insects and vertebrates. We find that the widespread extent of gene regulation by microRNAs is comparable between flies and mammals but that certain microRNAs may function in clade-specific modes of gene regulation. One of these microRNAs (miR-210) is predicted to contribute to the regulation of fly oogenesis. We also list specific regulatory relationships that appear to be conserved between flies and mammals. Our findings provide the most extensive microRNA target predictions in Drosophila to date, suggest specific functional roles for most microRNAs, indicate the existence of coordinate gene regulation executed by clustered microRNAs, and shed light on the evolution of microRNA function across large evolutionary distances. All predictions are freely accessible at our searchable Web site http://pictar.bio.nyu.edu.

MicroRNA genes are a recently discovered large class of small noncoding genes. These genes have been shown to regulate the expression of target genes by binding to partially complementary sites in the mRNAs of the targets. To understand microRNA function it is thus important to identify their targets. Here, the authors use their bioinformatic method, PicTar, and cross-species comparisons of several newly sequenced fly species to predict, genome wide, targets of microRNAs in Drosophila. They find that known fly microRNAs control at least 15% of all genes in D. melanogaster. They also show that genomic clusters of microRNAs are likely to coordinately regulate target genes. Analysis of the functional annotation of target genes furthermore suggests specific biological functions for many microRNAs. All predictions are freely accessible at http://pictar.bio.nyu.edu. Finally, Grün et al. compare the function of microRNAs across flies and mammals. They find that (a) the overall extent of microRNA gene regulation is comparable between both clades, (b) the number of targets for a conserved microRNA in flies correlates with the number of targets in mammals, (c) some conserved microRNAs may function in clade-specific modes of gene regulation, and (d) some specific microRNA–target regulatory relationships may be conserved between both clades.

Prediction and verification of microRNA targets by MovingTargets, a highly adaptable prediction method

BACKGROUND

MicroRNAs (miRNAs) mediate a form of translational regulation in animals. Hundreds of animal miRNAs have been identified, but only a few of their targets are known. Prediction of miRNA targets for translational regulation is challenging, since the interaction with the target mRNA usually occurs via incomplete and interrupted base pairing. Moreover, the rules that govern such interactions are incompletely defined.

RESULTS

MovingTargets is a software program that allows a researcher to predict a set of miRNA targets that satisfy an adjustable set of biological constraints. We used MovingTargets to identify a high-likelihood set of 83 miRNA targets in Drosophila, all of which adhere to strict biological constraints. We tested and verified 3 of these predictions in cultured cells, including a target for the Drosophila let-7 homolog. In addition, we utilized the flexibility of MovingTargets by relaxing the biological constraints to identify and validate miRNAs targeting tramtrack, a gene also known to be subject to translational control dependent on the RNA binding protein Musashi.

CONCLUSION

MovingTargets is a flexible tool for the accurate prediction of miRNA targets in Drosophila. MovingTargets can be used to conduct a genome-wide search of miRNA targets using all Drosophila miRNAs and potential targets, or it can be used to conduct a focused search for miRNAs targeting a specific gene. In addition, the values for a set of biological constraints used to define a miRNA target are adjustable, allowing the software to incorporate the rules used to characterize a miRNA target as these rules are experimentally determined and interpreted.

MicroRNA: biological and computational perspective

MicroRNAs (miRNAs) are endogenously expressed non-coding RNAs of 20-24 nucleotides, which post-transcriptionally regulate gene expression in plants and animals. Recently it has been recognized that miRNAs comprise one of the abundant gene families in multicellular species, and their regulatory functions in various biological processes are widely spread. There has been a surge in the research activities in this field in the past few years. From the very beginning, computational methods have been utilized as indispensable tools, and many discoveries have been obtained through combination of experimental and computational approaches. In this review, both biological and computational aspects of miRNA will be discussed. A brief history of the discovery of miRNA and discussion of microarray applications in miRNA research are also included.

Combinatorial microRNA target predictions

MicroRNAs are small noncoding RNAs that recognize and bind to partially complementary sites in the 3' untranslated regions of target genes in animals and, by unknown mechanisms, regulate protein production of the target transcript. Different combinations of microRNAs are expressed in different cell types and may coordinately regulate cell-specific target genes. Here, we present PicTar, a computational method for identifying common targets of microRNAs. Statistical tests using genome-wide alignments of eight vertebrate genomes, PicTar's ability to specifically recover published microRNA targets, and experimental validation of seven predicted targets suggest that PicTar has an excellent success rate in predicting targets for single microRNAs and for combinations of microRNAs. We find that vertebrate microRNAs target, on average, roughly 200 transcripts each. Furthermore, our results suggest widespread coordinate control executed by microRNAs. In particular, we experimentally validate common regulation of Mtpn by miR-375, miR-124 and let-7b and thus provide evidence for coordinate microRNA control in mammals.

A computational view of microRNAs and their targets

Small non-coding RNAs called microRNAs have been shown to play important roles in gene regulation across a broad range of metazoans from plants to humans. In this review, the nature and function of microRNAs will be discussed, with special emphasis on the computational tools and databases available to predict microRNAs and the genes they target.

The effect of RNA secondary structures on RNA-ligand binding and the modifier RNA mechanism: a quantitative model

RNA-ligand binding often depends crucially on the local RNA secondary structure at the binding site. We develop here a model that quantitatively predicts the effect of RNA secondary structure on effective RNA-ligand binding activities based on equilibrium thermodynamics and the explicit computations of partition functions for the RNA structures. A statistical test for the impact of a particular structural feature on the binding affinities follows directly from this approach. The formalism is extended to describing the effects of hybridizing small "modifier RNAs" to a target RNA molecule outside its ligand binding site. We illustrate the applicability of our approach by quantitatively describing the interaction of the mRNA stabilizing protein HuR with AU-rich elements. We discuss our model and recent experimental findings demonstrating the effectivity of modifier RNAs in vitro in the context of the current research activities in the field of non-coding RNAs. We speculate that modifier RNAs might also exist in nature; if so, they present an additional regulatory layer for fine-tuning gene expression that could evolve rapidly, leaving no obvious traces in the genomic DNA sequences.

Human MicroRNA targets

MicroRNAs (miRNAs) interact with target mRNAs at specific sites to induce cleavage of the message or inhibit translation. The specific function of most mammalian miRNAs is unknown. We have predicted target sites on the 3' untranslated regions of human gene transcripts for all currently known 218 mammalian miRNAs to facilitate focused experiments. We report about 2,000 human genes with miRNA target sites conserved in mammals and about 250 human genes conserved as targets between mammals and fish. The prediction algorithm optimizes sequence complementarity using position-specific rules and relies on strict requirements of interspecies conservation. Experimental support for the validity of the method comes from known targets and from strong enrichment of predicted targets in mRNAs associated with the fragile X mental retardation protein in mammals. This is consistent with the hypothesis that miRNAs act as sequence-specific adaptors in the interaction of ribonuclear particles with translationally regulated messages. Overrepresented groups of targets include mRNAs coding for transcription factors, components of the miRNA machinery, and other proteins involved in translational regulation, as well as components of the ubiquitin machinery, representing novel feedback loops in gene regulation. Detailed information about target genes, target processes, and open-source software for target prediction (miRanda) is available at http://www.microrna.org. Our analysis suggests that miRNA genes, which are about 1% of all human genes, regulate protein production for 10% or more of all human genes.

Right hepatic lobectomy in elderly patients with hepatocellular carcinoma

BACKGROUND/AIMS

The outcome of hepatectomy in elderly patients with hepatocellular carcinoma have been reported, however neither the morphological nor functional hepatic regeneration in elderly patients have been fully investigated.

MATERIALS AND METHODS

Fifty-six patients with hepatocellular carcinoma, who underwent a right hepatic lobectomy over an 8-year period, were classified into three groups according to their age; group 1 (n = 7), more than 70 years of age; group 2 (n = 40), patients from 50 to 69 years of age and group 3 (n = 9), under 50 years of age. There were no significant differences regarding backgrounds or intra-operative parameters among the three groups. The perioperative hepatic function, postoperative complications and the regeneration rate of the remnant left lobe at 1 month after operation were compared.

RESULTS

No differences were found in the regeneration rate, however, the levels of the hepaplastin test and lecithin:cholesterol acyltransferase at 7 days after hepatectomy in group 1 (31.3%, 8.8 U) were significantly lower than those in groups 2 and 3 (37.4%, 18.4 U; 47.9%, 29.4 U, respectively). The incidence of hospital death due to hepatic failure in group 1 (42.9%) was also significantly higher than that of group 2 (5.0%) or group 3 (0%).

CONCLUSION

The decline of postoperative protein synthesis regardless of the voluminal regeneration is a characteristic of the elderly. This phenomenon might thus be an important promoter of postoperative hepatic failure which remains unpredictable using any type of examination. Therefore, at this time, a major hepatectomy is not recommended as a viable treatment alternative in the elderly.